1. Field of the Invention
This invention relates generally to purchasing and reservation systems and, in particular, the present invention relates to improvement of yield management with respect to the group reservation of perishable commodities such as airline seats, hotel rooms and the like.
2. Description of the Related Art
Common carriers such as commercial buses, trains, and airlines, and service industries such as hotels and rental car companies, face complex issues when conducting strategic and operational planning. Each of these types of organizations deal with “perishable commodities” which are defined as commodities that cannot be inventoried and share three common characteristics: perishability, “fixed” capacity, and segmentability. Perishability means that each commodity ages or becomes unavailable, and thus has no value, after a certain date, time or similar temporal event (referred to herein as the “perishing date”). “Fixed” capacity implies a high cost of adding an incremental unit such that capacity is regarded as static and unchanging. Segmentability refers to the ability to segment customers based on a willingness to pay using different rates and/or different purchase restrictions, such as the date of purchase relative to the perishing date. Examples of perishable resources include airline seats, hotel room nights, rental car days and similar products or services such as described in L. R. Weatherford & S. E. Bodily, A Taxonomy and Research Overview of Perishable-Asset Revenue Management: Yield Management, Overbooking, and Pricing, 40 Operations Research 5, pp. 831-44 (1992), the disclosure of which is incorporated herein by reference.
Organizations marketing and selling perishable commodities spend numerous hours trying to choreograph the interrelated elements of scheduling, routing, and crew/staff rotations while maximizing profits and efficiency. Maximum profits are achieved when all of the available perishable commodities (e.g., with respect to airlines, all seats on a given flight) are sold on the perishing date (e.g., with respect to airlines, at the time the given flight departs). Maximum customer satisfaction occurs when perishable commodities reserved by consumers are available on the perishing date. The marketer/seller of perishable commodities must therefore constantly balance these two competing interests so that all of the commodities are sold and are available for all those who reserved them.
The terms “revenue management” and “yield management” are now common terms in service industry parlance to describe the use of statistical analysis to manage itinerary control, inventory control, over-booking and pricing so as to increase the revenue yield per unit of available capacity. Based on the statistical analysis, forecasting, optimization models, and the like, determinations are made as to which reservation requests to accept and which to reject in order to maximize revenues.
The airline industry presents a typical example of a service industry which utilizes yield management techniques to try to maximize profits while coping with the complicated operational issues inherent to the industry. It is a well-known practice in the airline industry to overbook flights in an attempt to assure that the flights are fully loaded with passengers on the perishing date, thereby maximizing the profits for the airlines. The policy of overbooking is based upon practical considerations. For various reasons, not all flights reserved are actually purchased, i.e., while they may have been reserved, they do not actually “materialize”.
One such reason relates to group bookings of “blocks” of seats in connection with, for example, a tour group or a large organization. Typically such reservations are made by a group coordinator 10-12 months in advance of the actual flight date. This means that the group coordinator must estimate the number of seats which will be needed for the block, and to assure that there are enough seats available for all those wishing to travel with the group, it is typical for the group coordinator to overestimate rather than underestimate the number of seats needed.
While providing convenience for the group coordinator, such reservation practices make it particularly difficult for airlines to assure that all flights depart without empty seats. For example, if the group coordinator waits until the last minute to inform the air carrier that less seats will be needed than were originally reserved, these unsold seats are considered unmaterialized reservations and the air carrier is suddenly left with seats which it may not be able to sell by the perishing date, resulting in a less-than-full flight. To compensate for unmaterialized reservations, airlines have adopted the policy of overbooking flights, particularly when the reservations are made by group coordinators who have a history of making group bookings having a low “materialization level,” i.e., having a high level of unmaterialized reservations. This practice is based on the understanding that a certain percentage of the seats on “reserved” status by the group coordinator will never actually materialize.
In a perfect world, the airlines could always tell with precision precisely how many seats a group coordinator would over-reserve for a particular flight and would then overbook for that flight by the exact number so that all seats would be filled. In reality, however, it is impossible to predict precisely how may reservations will not materialize; thus, airlines end up with either too few seats sold, thereby losing revenues by flying aircraft with empty seats, or too many seats sold, requiring the airlines to “bump” passengers onto the next available flight to their destination. While most airlines will in some manner compensate passengers that have been bumped, for example, by providing them with vouchers good towards future flights on the airline, free hotel accommodations, and the like, such a practice, is costly for the airlines, is usually extremely inconvenient to the airline traveler, and can lead to once-loyal passengers migrating to a competitor airline.
In an attempt to overcome the above problems, airlines may track the historical accuracy with which a particular group coordinator makes group reservations over a period of time. Based on the historical materialization level of the group coordinator as determined by these tracking methods, the point at which the particular flight(s) being reserved by the group coordinator is/are considered “closed” to additional bookings is increased to a number greater than 100% of the capacity of the aircraft, with the exact percentage greater than 100% being based upon the track record for that group coordinator.
The above-described tracking methods involve straight statistical analysis of the group coordinator's historical performance over a period of time. While the use of such methods provides assistance to the airlines, their focus is always on very general statistical history of a specific group coordinator and not on the factors that may cause a particular group reservation to be more accurate or less accurate. For example, many factors may cause a particular group booking to be more or less likely to fully materialize, including the country or countries involved in the booking; the number of seats being booked as a group; the complexity of the booking (e.g., does it also involve coordination with hotel stays and ground transportation as a “package deal”); and, with respect to itineraries involving multiple flight segments or flight “legs,” the number of different air carriers used in the itinerary. None of the prior art methods, however, analyze these or other similar details to allow a particular group reservation and/or group coordinator to be characterized as possessing certain traits which might identify reasons why a particular group reservation having certain characteristics is more likely to have a high materialization level than another, or to identify a particular group coordinator as possessing the ability to book one type of group booking with greater accuracy than another, different type of group booking.
The Applicant has determined, however, that it is only by understanding why a particular group booking has a high materialization level that better prediction models can be developed so as to optimize the yield management or revenue management system. If characteristics of the group coordinator making the reservations and/or the group booking itself were to be factored into the analysis, the effectiveness of the overbooking policy by the airlines could be increased. However, none of the prior art systems attempt to make such an analysis.
Accordingly, it would be desirable to have a method and system for gathering and storing information about prior reservations attributed to group bookings, details of the a current group reservation, and characteristics related to the group coordinator making the group reservation, and using this information to determine, with more precision than is available in the prior art, the materialization level of a pending current group reservation.